Senior Data Steward (DWH System Analyst)

Описание

This role involves owning and evolving data control processes, expanding model test coverage, managing access control, enhancing data catalogs, and leading data incident management, as well as gathering requirements and defining data governance standards.

Responsibilities

• Data Quality Control for Regulatory Reporting: Own and evolve the data control process by developing existing automated reconciliations, expanding completeness checks, and implementing quality gates prior to report submission
• DBT Data Testing: Expand model test coverage, monitor layer-to-layer discrepancies, and implement Data Contracts for critical data models
• Access Control & RLS Management: Maintain and enhance the role-based access model (RBAC) and Row-Level Security (RLS) across jurisdictions; manage regular access reviews as a repeatable procedure
• Data Catalog Enhancement: Set up lineage collection, assign dataset owners, maintain the business glossary of metrics, and promote its adoption across teams
• Data Incident Management: Lead complex data quality incident root-cause analysis (RCA) and adjust processes and checks to prevent recurrence
• Requirements Gathering & System Analysis: Collect business requirements from Business, Finance, and Compliance teams, translating them into detailed specifications for Data Engineering (data mapping, source descriptions, acceptance criteria)
• Data Governance Standards: Define and maintain data standards, including naming conventions, model documentation, and mandatory testing rules for critical layers

Requirements

• Strong SQL Proficiency: Ability to write heavy analytical queries, optimize slow query performance, and work with large-scale datasets
• Hands-on DBT Experience: Expertise in tests, sources, and model documentation; strong Git skills (commits, PRs, code reviews)
• Data Quality & Governance Expertise: Practical experience setting up DQ checks and metrics; hands-on experience with Data Catalogs (OpenMetadata, DataHub, or similar tools)
• Data Access Control Understanding: In-depth knowledge of access models, roles, RLS
• System Analysis Skills: Proven ability to translate business requirements into clear technical specifications and acceptance criteria
• Stakeholder Management: High degree of autonomy when communicating across teams (Data Engineering, Compliance, Finance)
• Python Skills: Python proficiency for automating DQ checks and interacting with metadata APIs

We offer

• Remote work
• Competitive salary, determined based on interview results
• Fully covered sick leave and vacation
• Work equipment provided
• 5/2 schedule with a flexible start to your workday
• Benefit package (sports, healthcare, education)
• Everything you need to succeed, support for your ideas and initiatives!

Hiring process

• Recruiter Screen: Our recruiters carefully review your application and reach out to schedule the initial interview. Feel free to ask more about the role!
• Hiring Manager Interview: Candidates selected undergo an interview where we discuss their skills, experience, and how they fit with corporate culture
• Assessment Task: Some candidates might complete a task to show their skills in action. Usually brief, these tasks respect your time
• Final Interview: This is the last step where you get feedback on your task and meet our department head
• Decision & Offer: We decide within 2 weeks and notify the chosen candidate with an offer to join us!